• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.113-116
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• 2008

This work presents numerical optimization for design of staggered arrays of dimples printed on opposite surfaces of a cooling channel with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization. As Pareto optimal front produces a set of optimal solutions, the trends of objective functions with design variables are predicted by hybrid multi-objective evolutionary algorithm. The problem is defined by three non-dimensional geometric design variables composed of dimpled channel height, dimple print diameter, dimple spacing and dimple depth to maximize heat transfer rate compromising with pressure drop. Twenty designs generated by Latin hypercube sampling were evaluated by Reynolds-averaged Navier-Stokes solver and the evaluated objectives were used to construct Pareto optimal front through hybrid multi-objective evolutionary algorithm. The optimum designs were grouped by k-mean clustering technique and some of the clustered points were evaluated by flow analysis. With increase in dimple depth, heat transfer rate increases and at the same time pressure drop also increases, while opposite behavior is obtained for the dimple spacing. The heat transfer performance is related to the vertical motion of the flow and the reattachment length in the dimple.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.10
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• pp.860-869
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• 2003

Design optimization of the heat sink with 7${\times}$7 square pin-fins is performed numerically using the Computational Fluid Dynamics (CFD) and the Computer Aided Optimization (CAO). In the pin-fins heat sink, the optimum design variables for fin height (h), fin width (w), and fan-to-heat sink distance (c) can be achieved when the thermal resistance ($\theta$$_{j}$) at the junction and the overall pressure drop ($\Delta$p) are minimized simultaneously. To complete the optimization, the finite volume method for calculating the objective functions, the BFGS method for solving the unconstrained non-linear optimization problem, and the weighting method for predicting the multi-objective problem are used. The results show that the optimum design variable for the weighting coefficient of 0.5 are as follows: w=4.653 mm, h=59.215 mm, and c=2.667 mm. In this case, the objective functions are predicted as 0.56K/W of thermal resistance and 6.91 Pa of pressure drop. The Pareto optimal solutions are also presented.re also presented.d.

• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.677-689
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• 2022

Generally, the goal of seismic retrofit design of an existing structure using energy dissipation devices is to determine the optimum design parameters of a retrofit device to satisfy a specified limit state with minimum cost. However, the presence of multiple parameters to be optimized and the computational complexity of performing non-linear analysis make it difficult to find the optimal design parameters in the realistic 3D structure. In this study, genetic algorithm-based optimal seismic retrofit methods for determining the required number, yield strength, and location of steel slit dampers are proposed to retrofit an asymmetric soft first-story structure. These methods use a multi-objective and single-objective evolutionary algorithms, each of which varies in computational complexity and incorporates nonlinear time-history analysis to determine seismic performance. Pareto-optimal solutions of the multi-objective optimization are found using a non-dominated sorting genetic algorithm (NSGA-II). It is demonstrated that the developed multi-objective optimization methods can determine the optimum number, yield strength, and location of dampers that satisfy the given limit state of a three-dimensional asymmetric soft first-story structure. It is also shown that the single-objective distribution method based on minimizing plan-wise stiffness eccentricity turns out to produce similar number of dampers in optimum locations without time consuming nonlinear dynamic analysis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.3 s.234
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• pp.455-461
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• 2005

This research studied robust design of composite hand for LTR (LCD glass Transfer Robot). $1^{st}$ DOE (Design of Experiment) was conducted to find out vital few Xs. 108 experiments were performed and their results were statistically analyzed. Pareto chart analysis shows that the geometric parameters (height and width of composite beam) are more important than material parameters $(E_{1},\;E_{2})$ or stacking sequence angle. Also, the stacking sequence of mid-layer is more important than that of outer-layer. The main effect plots shows that the maximum deflection of LTR hand is minimized with increasing height, width of beam and layer thickness. $2^{nd}$ DOE was conducted to obtain RSM (Response Surface Method) equation. 25 experiments were conducted. The CCD (Central Composite Design) technique with four factors was used. The coefficient of determination $(R^{2})$ for the calculated RSM equation was 0.989. Optimum design was conducted using the RSM equation. Multi-island genetic algorithm was used to optimum design. Optimum values for beam height, beam width, layer thickness and beam length were 24.9mm, 186.6mnL 0.15mm and 2402.4mm respectively. An approximate value of 0.77mm in deflection was expected to be a maximum under the optimum conditions. Six sigma robust design was conducted to find out guideline for control range of design parameter. To acquire six sigma level reliability, the standard deviation of design parameter should be con trolled within $2{\%}$ of average design value

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.4
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• pp.28-33
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• 2015

In this study, the optimal design for the support and the binding device for the protection of crops for the maximum allowable stress of the shape necessary to minimize volume has been proposed. Optimization of the support and the binding device for the crops should be designed to support businesses in terms of profit, in part to reduce the material, and to profit from the ease and speed of working that part of the farmers. We used CATIA for the mechanical design and the ANSYS program for the structural analysis. Additionally, the optimization was performed by PIAnO with seven design variables for the binding device and three parameters for the support. The weight method using a multi-objective function was also determined by the Pareto optimal solution. The volume of the binding device in the optimum design result was found to be reduced by 16%, from $2.278e-005m^3to1.912e-005m^3$. From the result, we confirmed the effectiveness of the design method proposed as a multi-objective function optimization problem.

• Smart Structures and Systems
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• v.16 no.1
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• pp.1-26
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• 2015

Minimizing construction cost and reducing seismic damage are two conflicting objectives in the design of any new structure. In the present work, we try to develop a framework in order to solve the optimum performance-based design problem considering the construction cost and the seismic damage of steel moment-frame structures. The Park-Ang damage index is selected as the seismic damage measure because it is one of the most realistic measures of structural damage. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. To improve the time efficiency of the proposed framework, three simplifying strategies are adopted: first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication; second, fitness approximation decreasing the number of fitness function evaluations; third, wavelet decomposition of earthquake record decreasing the number of acceleration points involved in time-history loading. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency's (FEMA) recommended seismic design specifications. The results from numerical application of the proposed framework demonstrate the efficiency of the framework in solving the present multi-objective optimization problem.

• Steel and Composite Structures
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• v.14 no.4
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• pp.397-408
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• 2013

This paper deals with multiobjective optimization of symmetrically laminated composite truncated circular conical shells subjected to external uniform pressure load and thermal load. The design objective is the maximization of the weighted sum of the critical buckling load and fundamental frequency. The design variable is the fibre orientations in the layers. The performance index is formulated as the weighted sum of individual objectives in order to obtain optimal solutions of the design problem. The first-order shear deformation theory (FSDT) is used in the mathematical formulation of laminated truncated conical shells. Finally, the effect of different weighting factors, length-to-radius ratio, semi-cone angle and boundary conditions on the optimal design is investigated and the results are compared.

• ETRI Journal
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• v.30 no.4
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• pp.535-545
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• 2008

This paper introduces a systematic top-down and bottom-up design methodology to assist the designer in the implementation of continuous-time (CT) cascade sigma-delta (${\Sigma}{\Delta}$) modulators. The salient features of this methodology are (a) flexible behavioral modeling for optimum accuracy-efficiency trade-offs at different stages of the top-down synthesis process, (b) direct synthesis in the continuous-time domain for minimum circuit complexity and sensitivity, (c) mixed knowledge-based and optimization-based architectural exploration and specification transmission for enhanced circuit performance, and (d) use of Pareto-optimal fronts of building blocks to reduce re-design iterations. The applicability of this methodology will be illustrated via the design of a 12-bit 20 MHz CT ${\Sigma}{\Delta}$ modulator in a 1.2 V 130 nm CMOS technology.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.4
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• pp.439-449
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• 2018

In this paper, multi-objective optimization of a multi-bubble pressure cabin in the underwater glider with Blended-Wing-Body (BWB) is carried out using Kriging and the Non-dominated Sorting Genetic Algorithm (NSGA-II). Two objective functions are considered: buoyancy-weight ratio and internal volume. Multi-bubble pressure cabin has a strong compressive capacity, and makes full use of the fuselage space. Parametric modeling of the multi-bubble pressure cabin structure is automatic generated using UG secondary development. Finite Element Analysis (FEA) is employed to study the structural performance using the commercial software ANSYS. The weight of the primary structure is determined from the volume of the Finite Element Structure (FES). The stress limit is taken into account as the constraint condition. Finally, Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) method is used to find some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. The best solution is compared with the initial design results to prove the efficiency and applicability of this optimization method.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1441-1446
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• 2003

The design optimization of the plate heat exchanger with staggered pin arrays for a fixed volume is performed numerically. The flow and thermal fields are assumed to be a streamwise-periodic flow and heat transfer with constant wall temperature and they are solved by using the finite volume method. The optimization is carried out by using the sequential linear programming (SLP) method and the weighting method is used for solving the multi-objective problem. The results show that the optimal design variables for the weighting coefficient of 0.5 are as follows; S=6.497mm, P=5.496mm, $D_1=0.689mm$, and $D_2=2.396mm$. The Pareto optimal solutions are also presented.